The microscopic models [1]}, [2]} that serve as the basis of our case study produce point-cloud data in the form of pigment-cell locations. As we show in Figure REF , stripes are visible in patterns generated by these models [1]}, [2]}, but the discrete nature of the data makes them challenging to quantitatively describe. To help address this, our methodology for quantifying stripe patterns in § draws on techniques from topological data analysis and computational geometry. Specifically, we utilize persistent homology and \(\alpha \) -shapes, which naturally lend themselves to point-cloud data. We provide an informal introduction to persistent homology and \(\alpha \) -shapes here; see [5]}, [6]}, [7]}, [8]}, [9]}, [10]} and [11]}, [12]}, respectively, for more technical details.
